PONE-D-21-13267

Measuring Social Mobility in Bangladesh: A Stochastic Modelling Approach

PLOS ONE

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Professor Hafiz T.A. Khan, Ph.D, CStat (UK) 

Academic Editor

PLOS ONE

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Reviewers' comments:

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Reviewer #1: No

Reviewer #2: Partly

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Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: The authors of this paper have attempted to analyze the social mobility in Bangladesh using the Markov Chain model. Scientific research related to social mobility in Bangladesh using a probabilistic approach is hardly seen in the existing literature, and filling this gap is the novelty of this work. However, I have some important comments regarding their work which are mentioned below:

(i) This study considers that the socio-economic conditions of offspring depend only on their father's socio-economic conditions. But in reality, offspring socio-economic conditions depend not only on their father's socio-economic conditions but also mother socio-economic conditions, sibling’s socio-economic conditions, gender, region and etc. Even this is evident in the descriptive statistics provided in Table 2. The authors may use multiple logistic regression as a very basic model before considering any sophisticated model which offers the flexibility to accommodate other covariates as well along with father's socio-economic conditions to model offspring socio-economic conditions.

(ii) Under the current Markov Chain framework where offspring socio-economic conditions depend only on their father's socio-economic conditions is treated as the simplest type of model to analyze social mobility (Borah. S (2013)). It would be really interesting work if authors can come up with new modelling tricks to model offspring socio-economic conditions which can take into account for other covariates as well.

Smita Borah, Stochastic Modelling of Social Mobility: A Case Study in Golaghat, Assam, International Journal of Statistics and Applications, Vol. 3 No. 3, 2013, pp. 43-49.

(iii) In Table 3, authors present a transition probability matrix for "Father to All". But the term "Father to All" is not defined anywhere before, which may make the reader confused. I guess they intended to mean all the children of a father belong to the same class at time t. For example, suppose a father has 3 children. Then all the three children will achieve the same education level at time t. If this is the case then it oversimplifies the real situation. If this is not the case then the Markov Chain does not seem applicable here.

(iv) Transition probability matrix for "Father to Son" has valid probabilistic interpretation when a father has only one son. If a father has more than one son then the Markov Chain framework fails to model this situation because of not having a valid transition probability matrix. For example, suppose in class 1 there are 15 fathers i.e. n_1=15. When one father has more than one son then ∑_(j=1)^5▒〖n_1j>15〗 which destroys the property of the transition probability matrix. Country like Bangladesh not having a stable population structure is very likely that every father has an average of more than one son. Under this condition, considering the Markov Chain to model offspring socio-economic conditions is not valid.

(v) Comment mentioned in (iv) also applicable for the transition probability matrix for "Father to Daughter"

Finally, I would like to recommend this paper for possible publication to PLOS ONE subject to the satisfactory major revision of the aforementioned points.

Reviewer #2: Upward social mobility, especially educational mobility, is an indication of improvement in a society. This nice work tries to evaluate intergenerational educational mobility in Bangladesh. The following suggestions will be helpful for improving the quality of the article.

1. Social mobility means mobility of different socio-economic factors across generations. This article deals with only one variable ‘educational status’. Here title is general but work is specific. Therefore, title should be specific like “Measuring Intergenerational Educational mobility in Bangladesh”. Again, Transition probability matrix (TPM) and Markov chain are well known stochastic approaches. So, name of the method should not mention in the title. It should be focused in methodology.

2. ‘Educational mobility’ should be highlighted in the 'introduction' especially in the objective of the study.

3. Rationale of the study should be clearly focused in the ending part of the “introduction”.

4. In Markov chain, state j and k should be matched each other. In this study, State ‘j’ represents “Father Education level” and state ‘k’ represents “offspring, son or daughter’s education level”. Here, Matching between two states is little bit confusing. Author’s reference articles are related with the intergenerational social classes (lower class, middle class, upper class etc.) which are more general and matched with each other in broader perspectives. It is better to refer work on intergenerational social mobility, especially educational mobility, between parents and offspring. Followings are some observations regarding this issue:

(i) Here transitions are: Father to all, Father to son, and father to daughter. I think limiting probability is possible to interpret Father to son only. Here, interpretation of limiting probabilities is not clear enough. It will be better to consider transition:

(a) Father to son (potential father)

(b) Mother to daughter (potential mother)

And then interpret the limiting probabilities.

(ii) For a stochastic matrix row sum must be unity. Please check the row sums in the matrices. Some miscalculations are as follows:

(a) 1st matrix (Father to all), row-5 (Table 3).

(b) 2nd matrix (Father to son), row-1 (Table 3).

(c) 3rd matrix (Father to daughter), row-1 (Table 3).

5. Some points to be noted:

(a) In table 2, column-2 label ‘Sable’ should be ‘stable’. Please correct it.

(b) “An illiterate father is three times less likely to send their sons to schools as compared to their daughters” (abstract: line no. 39-40). Without logistic regression model this finding is confusing. Please check t.

(c) Please check grammar especially comparative degree throughout the manuscript and correct accordingly.

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Reviewer #1: No

Reviewer #2: No

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Submitted filename: Reviewers Comments.pdf

Intergenerational Educational Mobility in Bangladesh

PONE-D-21-13267R1

Dear Authors,

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Kind regards,

Professor Hafiz T.A. Khan, Ph.D, CStat

Academic Editor

PLOS ONE

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